“SAP has an in-memory machine, you know, that’s a little bit smaller than what we offer,” Ellison said at OpenWorld yesterday, referring to SAP HANA and Oracle’s own all in-memory database Exadata X3, which debuted this week. “We have 26 terabytes of memory; [SAP offers] 0.5 terabytes of memory.”

In case you missed his point, Ellison put it as succinctly as he could: “The HANA in-memory machine is, like, really small.” (Hat Tip to eWeek)

So here we go with the “mine is bigger than yours” debate. I don’t particularly want to indulge Ellison, but he’s just plain wrong. I’ve covered SAP HANA extensively over the last year and a half, and yes there were initially questions about scaling HANA to multiple nodes. But earlier this year SAP, in conjunction with IBM, proved capable of doing just that, and a number of HANA customers currently store tens of terabytes of data in-memory across multiple nodes. That’s not sufficient for the Facebook’s of the world, but is more than adequate for most SAP customers and an in-memory database is just one of many elements needed in a comprehensive Big Data platform anyway.

But more importantly, Ellison’s attack on HANA’s manhood just flat misses two important points.

It’s About Business Value, Not Just Data Volume

One is that, while size matters in this the Era of Big Data, first and foremost enterprises want to know how vendors are going to help them turn all that data into valuable, actionable insights. That means Ellison would be better off using his bully pulpit to talk about Big Data use cases, illustrating how real-time Big Data analytics from Oracle allows enterprises to make smarter, faster decisions than the competition.

Bring on stage an online retail customer, for example, that is using Exadata to dynamically adjust pricing in real-time based on fast moving market conditions and customer demand. Or talk about a utility customer that is improving energy efficiency by analyzing data created by smart meters. How about a telecomm provider that is optimizing network traffic with predictive analytics or a financial services firm now able to detect and react to fraudulent activity in near real-time?

But that’s not what Ellison did. Instead he bloviated about Oracle’s theoretical data volume advantage. Now, contrast that with what we saw at SAPHIRE in May. In his keynote, SAP Co-CEO Bill McDermott brought out not one but three customers – Burberry, Ace Hardware and Coinstar — that are using HANA to transform the way they approach mission-critical business processes. The entire event was customer-focused in a way that Oracle OpenWorld simply was not. Ultimately, enterprise customers want to hear from and learn from their peers, not vendor CEOs, when it comes to applying Big Data in a way that delivers real business value – a lesson we at Wikibon have seen first hand.

The Call is Coming From Inside the Moscone Center

Ellison is also overlooking a threat to Oracle’s database business that I believe is just as serious, if not more so, than SAP HANA. That threat, of course, is the rapidly evolving open source Big Data ecosystem that is developing around technologies like Apache Hadoop, Cassandra and Solr.

I believe that Oracle, more than any other incumbent mega-vendor, has the most to lose in the Big Data Era. That’s because the open source, scale-out, commodity hardware approach to Big Data being made popular by DataStax, Cloudera and others is the antithesis of Oracle’s proprietary, scale-up, Sun-only hardware, take-it-or-leave-it approach. The former allows enterprise to use inexpensive (and often free) software on clusters of off-the-shelf boxes that scale linearly to process and analyze all types of data regardless of structure (or lack of structure). In Oracle land, enterprises that want to more power and volume pay the vendor for a bigger and bigger box that was originally designed with only relational data in mind.

I’m not suggesting that Oracle is going out of business any time soon, but in the long-term I believe it must find a more economically sustainable approach to Big Data, beyond its token Big Data Appliance. And Ellison may want to take a cue from one of OpenWorld’s own event sponsors, the aforementioned DataStax.

The San Mateo-based company, which just landed another $25 million in funding and was a “Gold” sponsor of Oracle’s annual event at the Moscone Center, brings together Cassandra, Hadoop and Solr in a single scale-out, Big Data platform. It supports both mission critical, real-time applications and large-scale batch analytics.

Today, data management technologies must be able to adjust to multiple data structures rather than adhering to a single, rigid single relational data model. DataStax, along with fellow Big Data upstarts Cloudera, Hortonworks, MapR and others, built its platform from the ground-up with this type of flexibility in mind. The problem for Oracle, whose legacy is in relational data, is that re-engineering systems to handle unstructured data after the fact is just plain difficult – both technologically and culturally.

Speaking inside theCUBE at OpenWorld, DataStax CEO Billy Bosworth put it this way (In the clip below, jump ahead to the 11:45 mark):

It’s hard to wholly change your DNA. It really is difficult. And you see this over and over and over again in the history of technology and now is a great time, by the way to go back and reread … Innovators Dilemma. Go back and reread that because you are seeing that exact kind of disruption model taking place in this world of Big Data and it’s a tough challenge [for legacy database vendors.] – Billy Bosworth, CEO, DataStax

Bosworth may as well have been speaking to Ellison directly. But that’s what Oracle must do – adapt to the new, open, scale-out approach to Big Data and do so without cannibalizing its existing business — if it wants to be as dominant in the database business 20 years from now as it has been for the last two decades. HANA is the more immediate threat to Oracle, but in the long-term DataStax and its like are the real challengers to the Big Data throne.

Great coverage of the great in-memory debate. I am with a new data storage firm, Tegile Systems. While we are not the juggernaut that Oracle is, we often get pulled into “mine is bigger than yours” stand-offs. Here’s the thing: we are big on de-duplication and compression here at Tegile. While intuitively, this helps customers save capacity on the rotating disk at the back-end of our arrays, it actually has a huge positive performance impact to applications such as databases. How? Our data reduction algorithms also save space in our DRAM and SSD space too – we use these as large read and write cache pools, respectively. So, if I can get a 5X data reduction ratio, I can also jam 5X mode data into cache, thus boosting cache hit ratios and drive performance much higher than what I might normally get with a traditional storage system.

Why bring this up on your post about Oracle and SAP? Only to warn readers that apples to apples comparisons are even harder to assemble today than they ever have been before. Simply looking at the cache capacity of our mid-range arrays that have between 600GB to 4.4TB of SSD in them doesn’t do the architecture justice. Customers need to demand an in-house proof of concept to put the “your mileage may vary” weasel words to rest. Arm waving during the keynote of a conference means little to nothing (and I’m a marketing guy!)

Again, thank you for the great coverage, Jeff.

Rob

bugoff1234

Now this is an weird comment… are you advertising something Rob?

I do commend you for asking for a POC, but many other of my IT administrator peers would agree I don’t always have time for POCs. I’ve got my day job to do. Do you guys have validated designs?

Rob Commins

My apologies if I came across as an informercial for our wares. My intent is to be very up front about the position I was writing from. I do recognize that my comment is a bit tangential, but we see so many vendors making claims (as Ellison did vs SAP) that have little or nothing to do with what a customer will see in production, I felt compelled to post my comment with anecdotal examples I know from my day to day business. We do indeed have reference architectures and best practice guidance we’ve assembled from customer’s real world production feedback. If your schedule does not permit your own POC, I suggest customers looking at new technology press vendors for those real world examples and leverage references from end users to validate those claims. Hope that helps.